Median regression model with doubly truncated data

We study the problem of fitting a heteroscedastic median regression model with doubly truncated data. A self-consistency equation is proposed to obtain an estimator. We set up a least absolute deviation estimating function. We establish the consistency and asymptotic normality for the case when covariates are discrete. The finite sample performance of the proposed estimators are investigated through simulation studies. The proposed method is illustrated using the AIDS Blood Transfusion Data.     

Methodology and analysis for comparing discrete linear l1 approximation codes

This is the first of a projected series of papers dealing with computational experimentation in mathematical programming. This paper provides early results of a test case using four discrete linear L₁ approximation codes. Variables influencing code behavior are identified and measures of performance are specified. More importantly, an experimental design is developed for assessing code performance and is illustrated using the variable “problem size”.     

Recursive M-estimators of location

This paper deals with recursive M-estimators of a location parameter θ in stationary processes when scale is regarded as a nuisance parameter. For the nonrecursive M-estimators, the median absolute deviation is a useful estimator of scale. Two recursive variants of the median absolute deviation are proposed and the performance of the resulting recursive estimators is examined in a numerical study.     

A comparison of robust regression techniques for the estimation of weibull parameters

In this paper several alternative robust reqression techniques are compared for estimating parameters of a Weibull distribution . In addition to the usual least squares (L₂) and least absolute deviation (L₁) methods, a number of one-step reweighting schemes based on the L₁residuals are considered. The results of an extensive series of Monte Carlo simulation experiments demonstrate that the Anscmbe reweighting scheme generally produces the best Weibull estimates over the range of sample sizes and parameter values studied.     

Perturbation analysis for the minimum sum of absolute errors regression

In this paper we study the effect of independent and simultaneous changes in the values of the response variable for all the observations on the minimum sum of absolute errors (or for brevity absolute errors) regression. We develop an algorithm to determine the maximum amount by which the values of the response variable can change without changing the absolute errors regression hyperplane. We illustrate the results with an example.     

Sharp bounds on l-estimates and their expectations for dependent samples

Sharp bounds on the expectation of each L-estimate are determined for samples of identically distributed random variables with a given expectation and a central absolute moment of order p > 1, The distributions achieving these bounds are constructed. Analogous results are derived in the cases of symmetric, noraiegative and bounded random variables, Accurate bounds for L-estimates of arbitrary finite samples are concluded.     

Ethical Decision-Making in the Helping Profession

Abstract

First, we examine several of the more prominent theoretical approaches in ethics (the utilitarian, absolute rule, principle based, and ethics of care approaches) and find the principle-based, common morality approach, and the ethics of care approach to be the two approaches that are most relevant to the types of ethical decisions practitioners characteristically are confronted with in a social work setting. We then propose combining these two approaches, taking into consideration the advantages and drawbacks of each, such that in application these two approaches can be seen to complement one another. We show in two brief hypothetical cases how the combined approach can be used to guide practitioners' ethical decision-making in real life situations.     

Coefficients of determinations for variable selection in the msae regression

Our objective is to modify a robust coefficient of determination for the minimum sum of absolute errors MSAE regression proposed by McKean and Sievers (1987) so that it satisfies all the desirable properties. We also propose an adjusted coefficient of determination that is appropriate for comparing several models with different number of variables. Further, it has the property that if it decreases with the addition of predictor variables to the model, then the contribution of these variables is statistically non-significant. We illustrate the results with an example.     

Estimating the minimum and maximum location parameters for two ig-exponential scale mixtures

Suppose that we have two components, each having a two-parameter exponential distribution. Suppose further that these components are conditionally independent, sharing a common random hazard rate and possessing unequal, fixed, unknown location parameters. We develop estimators for the minimum and maximum of these location parameters when the random hazard rate has an inverse Gaussian distribution. Performance comparisons are made among the proposed estimators. Maximum likelihood estimators are shown to be inadmissible.     

王弼《周易注》“刚柔”观略探

王弼运用"刚柔"这对范畴来说明和解释政治哲学观念以及阐释各类人事现象,极大的丰富和发展了《周易》刚柔观:王弼在刚柔性质和政治哲学领域崇刚抑柔,在统治策略和人事行动方面也强调要有一定的刚性,但他又坚决反对片面的、无原则的追求刚性;同时,强调柔顺的一面,要求统治阶级居尊以柔,虚己待人。在修家养身等道德方面,王弼推崇刚正之道,在圣人治化方面却强调柔的一面。